Antenna diversity is widely employed in base station receivers to improve uplink performance. The redundancy that is provided by the multiple antennas can be utilized in a variety of interference suppression techniques of varying complexity.
For example, in the 3GPP standard long term evolution (LTE) single-carrier frequency-division multiple access (SC-FDMA) is utilized as the uplink access technology and frequency domain equalization (FDE) is a necessary receiving technique in SC-FDMA to mitigate the interference caused by multi-path propagation. One type of receiver used for this purpose is the so-called interference-rejection-combining (IRC) receiver. In an IRC receiver, linear minimum mean square error (MMSE) antenna combining is performed in the frequency domain followed by frequency domain equalization.
In some more detail, as the skilled person will realize, in order to perform linear MMSE antenna combining, impairment co-variance is estimated on each sub-carrier in addition to the channel estimation. The basic impairment covariance estimate can be based on channel estimates for a number of sub-carriers, typically one resource block (RB). Averaging of multiple basic covariance estimates can be performed to reduce the impact of noise further. Then the inverse matrix of impairment co-variance is used for each sub-carrier to calculate weights for use in MMSE antenna combining.
In the prior art, impairment co-variance estimation is typically performed by averaging the basic co-variance estimate over a set of sub-carriers, say 12 sub-carriers in one RB. It is a relatively simple process and it works reasonably well with 2-antenna reception. However the performance gap from an ideal IRC receiver is too large, as will be illustrated in further detail below, if the number of receiving antennas are large, for example 8.
Furthermore, another issue with many IRC receivers in the prior art is the complexity of matrix inversion, especially when many receiving antennas are involved and large bandwidth is allocated. Needless to say, an 8×8 matrix inversion is much more complicated than a 2×2 matrix inversion.